Ph.D. July, 2005, Statistics, University of Missouri-Columbia, USA
B.S. August, 1999, Statistics, Ewha Womans University, Korea
Employment
2015 - 2025, Associate Professor, Department of Mathematics and Statistics, University of Maryland, Baltimore County, USA
2019 - 2021 Visiting Professor, Department of Statistics, Seoul National University, Korea
2016, Visiting Scholar, Computational Biology Branch, National Center for Biotechnology Information, National Institute of Health, USA
2009 - 2015, Assistant Professor, Department of Mathematics and Statistics, University of Maryland, Baltimore County, USA
2005 - 2008, Assistant Professor, Department of Mathematics and Statistics, University of Nevada, Reno, USA
My research includes both theoretical and applied statistics, with a strong emphasis on developing novel methodologies motivated by important problems in biological applications. I have worked on longitudinal data analysis and survival analysis problems and one of the newer research areas that I have been exploring is high-dimensional data analysis. This area has played a crucial role in statistics and related areas such as bioinformatics and genomics. In particular, motivated by collaborative work with colleagues in biological sciences, we developed several multiple testing procedures for various settings. As a biostatistician, I thrived in interdisciplinary environments, working closely with researchers from diverse fields to translate statistical theory into impactful solutions for complex real-world problems.
Field of interest: Longitudinal Data Analysis, Survival Analysis, Semiparametric and Nonparametric Methods, and High Dimensional Multiple Testing
Selected Publications:
- Seohwa Hwang, Mark Ramos, DoHwan Park, Junyong Park, Johan Lim, and Erin M. Green. Two-Stage Multiple Test Procedures Controlling FDR with auxiliary variable and their Application to Set4∆ Mutant Data. Biometrical Journal, accepted.
- Seonghun Cho, Youngrae Kim, Johan Lim, Hyungwon Choi, DoHwan Park, and Wonchul Jang. Multiple Testing of One-Sided Hypotheses under General Dependence. Statistica Sinica, accepted.
- Iris Ivy M. Gauran∗, Junyong Park, Ilia Rattsev, Thomas A. Peterson, Maricel G. Kann, DoHwan Park. September 2022. Bayesian Local False Discovery Rate for sparse count data with application to the discovery of hotspots in protein domains. Annals of Applied Statistics. 16(3), 1459–1475.
- Mark Ramos, DoHwan Park, Johan Lim, Junyong Park, Khoa Tran, Eric Garcia, and Erin M. Green. December 2021. Adaptive local false discovery rate procedures for highly spiky data and their application RNA sequencing data of yeast SET4 deletion mutants. Biometrical Journal. 63(8), 1729–1744.